code: def _GenerateTestData(self, matrix_shape, num_rhs):
      batch_shape = matrix_shape[:-2]
      matrix_shape = matrix_shape[-2:]
      assert matrix_shape[0] == matrix_shape[1]
      n = matrix_shape[0]
      matrix = np.ones(matrix_shape).astype(np.float32) / (
          2.0 * n
      ) + np.diag(np.ones(n).astype(np.float32))
      rhs = np.ones([n, num_rhs]).astype(np.float32)
      matrix = variables.Variable(
          np.tile(matrix, batch_shape + (1, 1)), trainable=False
      )
      rhs = variables.Variable(
          np.tile(rhs, batch_shape + (1, 1)), trainable=False
      )
      return matrix, rhs
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the MatrixSolveBenchmark obj's underlying member method code with example usage: obj._GenerateTestData(matrix_shape, num_rhs) and returns: matrix,  rhs